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Dynamic hand gesture recognition algorithm based on depth information

YU Jing1, TIAN Guohui1*, YIN Jianqin2   

  1. 1. School of Control Science and Engineering, Shandong University, Jinan 250061, Shandong, China;
    2.  Shandong Provincial Key Laboratory of Network Based Intelligent Computing,
    School of Information Science and Engineering,  University of Jinan, Jinan 250022, Shandong, China
  • Received:2013-12-11 Online:2014-06-20 Published:2013-12-11

Abstract: To solve the complex calculation and the unreliable feature extraction of gesture recognition, a fast algorithm of dynamic gesture recognition based on the depth information of Kinect was proposed. Firstly,the depth camera of Kinect was used to get the depth image. Then, the method of threshold segmentation was used for image preprocessing, using OpenCV library and depth information to extract the foreground. Finally, Dynamic time warping algorithm calculated the similarity between test behavior template and reference behavior template for classifying the samples. The algorithm was realized under VS2010 by integrating OpenNI and OpenCV. Compared with other algorithms, this algorithm improved the extraction method of the dynamic gesture characteristics and the classification trajectory. Experimental results showed that the proposed method had a high recognition rate for the dynamic hand gestures with characteristics of time and space, and it had robustness under different illumination and complex background.

Key words: depth information, dynamic time warping, behavior representation characteristic, Kinect, gesture recognition

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